A Fermatean Fuzzy Decision Support Framework for Wireless Technology Selection in Disaster Management

Authors

  • Karahan Kara Department of Data Science and Analytics, Faculty of Economics and Administrative Sciences, İzmir Katip Çelebi University, 35620 İzmir, Türkiye; Department of Engineering, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences, SIMATS, Chennai, India; Department of Business, Faculty of Economics and Administrative Sciences, OSTIM Technical University, 06374 Ankara, Türkiye. https://orcid.org/0000-0002-1359-0244
  • Galip Cihan Yalçın Department of Business, Faculty of Economics and Administrative Sciences, OSTIM Technical University, 06374 Ankara, Türkiye. https://orcid.org/0000-0001-9348-0709
  • Çağatay Korkuç Department of Electrical and Electronic Engineering, Faculty of Engineering, Gazi University, 06570 Ankara, Türkiye https://orcid.org/0000-0003-0007-2154
  • Yasin Genç Department of Electrical and Electronic Engineering, Faculty of Engineering, Gazi University, 06570 Ankara, Türkiye. https://orcid.org/0000-0003-2271-9668
  • Vladimir Simic Department of Computer Science and Engineering, College of Informatics, Korea University, 145 Anam-ro, Seongbuk-gu, Seoul 02841, Republic of Korea; Department of Industrial Engineering, Faculty of Engineering, Dogus University, 34775 Umraniye, Istanbul, Türkiye; Center for Digital Transformation and Artificial Intelligence Research, Bahçeşehir Cyprus University, Nicosia, TRNC Mersin 10, Northern Cyprus. https://orcid.org/0009-0003-5836-6881
  • Erkan Afacan Department of Electrical and Electronic Engineering, Faculty of Engineering, Gazi University, 06570 Ankara, Türkiye. https://orcid.org/0000-0003-4025-6847
  • Hasan Dinçer School of Business, Istanbul Medipol University, 34810 İstanbul, Türkiye; Research Center for Sustainable Economic Development, Khazar University, Baku, Azerbaijan. https://orcid.org/0000-0002-8072-031X
  • Serhat Yüksel School of Business, Istanbul Medipol University, 34810 İstanbul, Türkiye; Research Center for Sustainable Economic Development, Khazar University, Baku, Azerbaijan. https://orcid.org/0000-0002-9858-1266
  • Dragan Pamucar Department of Operations Research and Statistics, Faculty of Organizational Sciences, University of Belgrade, Belgrade, Serbia; UNEC Applied Artificial Intelligence Research Center, Azerbaijan State University of Economics (UNEC), Baku, Azerbaijan; Faculty of Engineering and Technology, Sunway University, No. 5, Jalan Universiti, 47500 Selangor Darul Ehsan, Malaysia. https://orcid.org/0000-0001-8522-1942

DOI:

https://doi.org/10.54327/set2026/v6.iS1.377

Keywords:

Disaster Logistics, Wireless Technology Selection, Fermatean Fuzzy Sets, Ranking Comparison Method, Alternative Ranking Using Two-Step Logarithmic Normalization Method

Abstract

Wireless technologies increasingly enable effective communication in disaster management. This study proposes a novel hybrid framework for selecting wireless technologies in disaster management. The proposed approach is called the Fermatean fuzzy (FF)–Maclaurin–Ranking Comparison Method (RANCOM)–Entropy–Alternative Ranking Using Two-Step Logarithmic Normalization (ARLON) hybrid method. FF sets capture the ambiguity and vagueness in experts' judgments. At the same time, RANCOM and Entropy determine the subjective and objective importance of the evaluation criteria, respectively. The ARLON method ranks wireless technologies based on performance. Furthermore, the Maclaurin-based aggregation operator combines expert evaluations. The study demonstrates the application through a case study in Türkiye, focusing on wireless technology selection to enhance disaster management capabilities following recent major earthquakes. A panel of nine experts with extensive knowledge of disaster management and wireless communication technologies participated in the evaluation process. The assessment considered twelve performance criteria and eight wireless technology alternatives. The results indicate that 5G RedCap is the most suitable wireless technology for the case study. In addition, the most important criterion was "ease of use/setup”. Finally, sensitivity and comparative analyses confirm the proposed framework's robustness and reliability.

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Published

23.09.2026

Data Availability Statement

Available on request from the corresponding author.

How to Cite

[1]
K. Kara, “A Fermatean Fuzzy Decision Support Framework for Wireless Technology Selection in Disaster Management”, Sci. Eng. Technol., vol. 6, no. S1, pp. 170–194, Sep. 2026, doi: 10.54327/set2026/v6.iS1.377.

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